Helsinki-NLP-opus-mt-en-de-fine-tuned
This model is a fine-tuned version of Helsinki-NLP/opus-mt-en-de on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.4012
- Bleu: 26.4813
- Gen Len: 30.4441
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 32
- eval_batch_size: 128
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|---|---|---|---|---|---|
| No log | 0.5714 | 1000 | 1.4256 | 26.2617 | 30.4794 |
| 1.5134 | 1.1429 | 2000 | 1.4151 | 26.3567 | 30.4671 |
| 1.5134 | 1.7143 | 3000 | 1.4098 | 26.4796 | 30.5562 |
| 1.4419 | 2.2857 | 4000 | 1.4061 | 26.4878 | 30.4188 |
| 1.4419 | 2.8571 | 5000 | 1.4040 | 26.4833 | 30.4619 |
| 1.3995 | 3.4286 | 6000 | 1.4023 | 26.4792 | 30.4654 |
| 1.3995 | 4.0 | 7000 | 1.4009 | 26.5708 | 30.4757 |
| 1.3715 | 4.5714 | 8000 | 1.4012 | 26.4813 | 30.4441 |
Framework versions
- Transformers 4.57.2
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
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Helsinki-NLP/opus-mt-en-de